Overlap matrix GREAT
Library
Data
load("input/overlap_tables.RData")
mat$anno1 <- "no"
mat$anno1[mat$class == "proximal <=1000bp" | mat$class == "TSS"] <- "Proximal_1000_TSS"
mat$anno1[mat$class == "intronic" | mat$class == "exonic"] <- "intronic_exonic"
list_s1 <- lapply(sp_df_s1, function(x) inner_join(mat, x))
list_s2 <- lapply(sp_df_s2, function(x) inner_join(mat, x))Function
perform_rGREAT <- function(df, rna = FALSE, bg, fName = "no_ChIP_data", split = FALSE, sp_col = "class", outDir = NULL, rnaCutoff = FALSE) {
if (nrow(df) > 10) {
od <- paste0("./output/", outDir)
if (!dir.exists(od)) {
dir.create(od)
}
d <- NULL
if (rna) {
if (rnaCutoff) {
d <- df
d$rna <- (abs(d$RNA_PND15_vs_Adult_logFC) >= 1) & (d$RNA_PND15_vs_Adult_adj.P.Val <= 0.05)
d$rna <- tolower(d$rna)
d$rna[is.na(d$rna)] <- "not_detected"
d <- split(x = d, f = d$rna)
} else {
d <- df
d$rna <- (abs(d$RNA_PND15_vs_Adult_logFC) >= 0) & (d$RNA_PND15_vs_Adult_adj.P.Val >= 0)
d$rna <- tolower(d$rna)
d$rna[is.na(d$rna)] <- "not_detected"
d <- split(x = d, f = d$rna)
}
} else {
d <- list(df)
names(d) <- fName
}
sp_d <- NULL
try(
if (split) {
e <- lapply(d, function(x) {
x[, sp_col] <- gsub(
pattern = " ", replacement = "_",
x = x[, sp_col]
)
x[, sp_col] <- gsub(
pattern = "<=", replacement = "",
x = x[, sp_col]
)
sp_d <- split(x, x[, sp_col])
sp_d <- sp_d[names(sp_d) != "no"]
names(sp_d) <- paste(fName, names(sp_d), sep = "-")
return(sp_d)
})
sp_d <- e
} else {
sp_d <- list(d)
names(sp_d) <- fName
}
)
try(
great <- mclapply(sp_d, function(x) {
res <- mclapply(x, function(y) {
df_GR <- GRanges(y)
set.seed(123)
bed <- data.frame(df_GR, stringsAsFactors = F)
bed <- bed[substr(x = bed$seqnames, start = 1, stop = 3) == "chr", ]
job <- submitGreatJob(gr = bed, bg = bg, species = "mm10")
tb <- getEnrichmentTables(job)
return(list(table = tb, job = job))
}, mc.preschedule = F, mc.cores = length(x))
return(res)
}, mc.preschedule = F, mc.cores = length(sp_d))
)
try(
if ((split & rna) | rna) {
for (i in 1:length(great)) {
n <- names(great)[i]
for (j in 1:length(great[[i]])) {
n1 <- names(great[[i]])[j]
names(great[[i]])[j] <- paste(n1, n, sep = "-")
}
}
}
)
try(
tmp <- mclapply(great, function(x) {
for (i in 1:length(x)) {
tb <- x[[i]]$table
n <- names(x)[i]
writexl::write_xlsx(
x = tb$`GO Molecular Function`,
path = paste0("output/", outDir, "/", n, "_GO_MF.xlsx"),
col_names = T, format_headers = T
)
writexl::write_xlsx(
x = tb$`GO Biological Process`,
path = paste0("output/", outDir, "/", n, "_GO_BP.xlsx"),
col_names = T, format_headers = T
)
writexl::write_xlsx(
x = tb$`GO Cellular Component`,
path = paste0("output/", outDir, "/", n, "_GO_CC.xlsx"),
col_names = T, format_headers = T
)
}
}, mc.preschedule = F, mc.cores = length(great))
)
try(return(great))
}
}Background all regions
load("input/atac_diff_chromatin_accessibility.RData")
bg_all <- data.frame(data@rowRanges, check.names = F, stringsAsFactors = F)[, c(1:5, 11)]
bg_all <- bg_all[substr(x = bg_all$seqnames, start = 1, stop = 3) == "chr", ]
colnames(bg_all) <- gsub(pattern = "Peak.", replacement = "", x = colnames(bg_all))
rownames(bg_all) <- bg_all$NameAnalysis
Without ChIP data
no_ChIP <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_", names(list_s1)[i])
no_ChIP[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = FALSE,
bg = bg,
fName = n,
split = FALSE,
outDir = "no_ChIP",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%no_ChIP_split <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_", names(list_s1)[i])
no_ChIP_split[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = FALSE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "no_ChIP_split",
rnaCutoff = FALSE
)
}no_ChIP_split_a <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_", names(list_s1)[i])
no_ChIP_split[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = FALSE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "no_ChIP_split_AnnoMerged",
rnaCutoff = FALSE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%no_ChIP_rna <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_rna_", names(list_s1)[i])
no_ChIP_rna[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = FALSE,
outDir = "no_ChIP_rna",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%no_ChIP_split_rna <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_", names(list_s1)[i])
no_ChIP_split_rna[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "no_ChIP_split_rna",
rnaCutoff = FALSE
)
}no_ChIP_split_rna_a <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_", names(list_s1)[i])
no_ChIP_split_rna[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "no_ChIP_split_rna_AnnoMerged",
rnaCutoff = FALSE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%no_ChIP_rna_cutoff <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_rna_cutoff_", names(list_s1)[i])
no_ChIP_rna_cutoff[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = FALSE,
outDir = "no_ChIP_rna_cutoff",
rnaCutoff = TRUE
)
}##
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|======================================================================| 100%no_ChIP_split_rna_cutoff <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_cutoff", names(list_s1)[i])
no_ChIP_split_rna_cutoff[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "no_ChIP_split_rna",
rnaCutoff = TRUE
)
}no_ChIP_split_rna_cutoff_a <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_cutoff", names(list_s1)[i])
no_ChIP_split_rna_cutoff[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "no_ChIP_split_rna_AnnoMerged",
rnaCutoff = TRUE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%no_ChIP_bg_all <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_", names(list_s1)[i])
no_ChIP_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = FALSE,
bg = bg_all,
fName = n,
split = FALSE,
outDir = "no_ChIP_bg_all",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%no_ChIP_split_bg_all <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_", names(list_s1)[i])
no_ChIP_split_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = FALSE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "no_ChIP_split_bg_all",
rnaCutoff = FALSE
)
}no_ChIP_split_bg_all_a <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_", names(list_s1)[i])
no_ChIP_split_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = FALSE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "no_ChIP_split_bg_all_AnnoMerged",
rnaCutoff = FALSE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%no_ChIP_rna_bg_all <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_rna_", names(list_s1)[i])
no_ChIP_rna_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = FALSE,
outDir = "no_ChIP_rna_bg_all",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%no_ChIP_split_rna_bg_all <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_", names(list_s1)[i])
no_ChIP_split_rna_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "no_ChIP_split_rna_bg_all",
rnaCutoff = FALSE
)
}no_ChIP_split_rna_bg_all_a <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_", names(list_s1)[i])
no_ChIP_split_rna_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "no_ChIP_split_rna_bg_all_AnnoMerged",
rnaCutoff = FALSE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%no_ChIP_rna_cutoff_bg_all <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_rna_cutoff_", names(list_s1)[i])
no_ChIP_rna_cutoff_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = FALSE,
outDir = "no_ChIP_rna_cutoff_bg_all",
rnaCutoff = TRUE
)
}##
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|======================================================================| 100%no_ChIP_split_rna_cutoff_bg_all <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_cutoff", names(list_s1)[i])
no_ChIP_split_rna_cutoff_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "no_ChIP_split_rna_bg_all",
rnaCutoff = TRUE
)
}no_ChIP_split_rna_cutoff_bg_all_a <- list()
for (i in 1:length(list_s1)) {
n <- paste0("no_ChIP_split_rna_cutoff", names(list_s1)[i])
no_ChIP_split_rna_cutoff_bg_all[[n]] <- perform_rGREAT(
df = list_s1[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "no_ChIP_split_rna_bg_all_AnnoMerged",
rnaCutoff = TRUE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%With ChIP data
with_ChIP <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_", names(list_s2)[i])
with_ChIP[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = FALSE,
bg = bg,
fName = n,
split = FALSE,
outDir = "with_ChIP",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_split <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_", names(list_s2)[i])
with_ChIP_split[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = FALSE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "with_ChIP_split",
rnaCutoff = FALSE
)
}with_ChIP_split_a <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_", names(list_s2)[i])
with_ChIP_split[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = FALSE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "with_ChIP_split_AnnoMerged",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_rna <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_rna_", names(list_s2)[i])
with_ChIP_rna[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = FALSE,
outDir = "with_ChIP_rna",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_split_rna <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_", names(list_s2)[i])
with_ChIP_split_rna[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "with_ChIP_split_rna",
rnaCutoff = FALSE
)
}with_ChIP_split_rna_a <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_", names(list_s2)[i])
with_ChIP_split_rna[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "with_ChIP_split_rna_AnnoMerged",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_rna_cutoff <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_rna_cutoff_", names(list_s2)[i])
with_ChIP_rna_cutoff[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = FALSE,
outDir = "with_ChIP_rna_cutoff",
rnaCutoff = TRUE
)
}##
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|======================================================================| 100%with_ChIP_split_rna_cutoff <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_cutoff_", names(list_s2)[i])
with_ChIP_split_rna_cutoff[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "with_ChIP_split_rna_cutoff",
rnaCutoff = TRUE
)
}with_ChIP_split_rna_cutoff_a <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_cutoff_", names(list_s2)[i])
with_ChIP_split_rna_cutoff[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg,
fName = n,
split = TRUE,
sp_col = "anno1_AnnoMerged",
outDir = "with_ChIP_split_rna_cutoff",
rnaCutoff = TRUE
)
}## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
## Error in `[.data.frame`(x, , sp_col) : undefined columns selected
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not foundwith_ChIP_bg_all <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_bg_all_", names(list_s2)[i])
with_ChIP_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = FALSE,
bg = bg_all,
fName = n,
split = FALSE,
outDir = "with_ChIP_bg_all",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_split_bg_all <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_bg_all_", names(list_s2)[i])
with_ChIP_split_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = FALSE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "with_ChIP_split_bg_all",
rnaCutoff = FALSE
)
}with_ChIP_split_bg_all_a <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_bg_all_", names(list_s2)[i])
with_ChIP_split_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = FALSE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "with_ChIP_split_bg_all_AnnoMerged",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_rna_bg_all <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_rna_bg_all_", names(list_s2)[i])
with_ChIP_rna_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = FALSE,
outDir = "with_ChIP_rna_bg_all",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_split_rna_bg_all <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_bg_all_", names(list_s2)[i])
with_ChIP_split_rna_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "with_ChIP_split_rna_bg_all",
rnaCutoff = FALSE
)
}with_ChIP_split_rna_bg_all_a <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_bg_all_", names(list_s2)[i])
with_ChIP_split_rna_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "with_ChIP_split_rna_bg_all_AnnoMerged",
rnaCutoff = FALSE
)
}##
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|======================================================================| 100%with_ChIP_rna_cutoff_bg_all <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_rna_cutoff_bg_all_", names(list_s2)[i])
with_ChIP_rna_cutoff_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = FALSE,
outDir = "with_ChIP_rna_cutoff_bg_all",
rnaCutoff = TRUE
)
}##
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|======================================================================| 100%with_ChIP_split_rna_cutoff_bg_all <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_cutoff_bg_all_", names(list_s2)[i])
with_ChIP_split_rna_cutoff_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "class",
outDir = "with_ChIP_split_rna_cutoff_bg_all",
rnaCutoff = TRUE
)
}with_ChIP_split_rna_cutoff_bg_all_a <- list()
for (i in 1:length(list_s2)) {
n <- paste0("with_ChIP_split_rna_cutoff_bg_all_", names(list_s2)[i])
with_ChIP_split_rna_cutoff_bg_all[[n]] <- perform_rGREAT(
df = list_s2[[i]],
rna = TRUE,
bg = bg_all,
fName = n,
split = TRUE,
sp_col = "anno1",
outDir = "with_ChIP_split_rna_cutoff_bg_all_AnnoMerged",
rnaCutoff = TRUE
)
}##
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## Error in names(sp_d) <- paste(fName, names(sp_d), sep = "-") :
## 'names' attribute [1] must be the same length as the vector [0]
## Error in mclapply(sp_d, function(x) { : 'mc.cores' must be >= 1
## Error in try(if ((split & rna) | rna) { : object 'great' not found
## Error in mclapply(great, function(x) { : object 'great' not found
## Error in try(return(great)) : object 'great' not found
##
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|======================================================================| 100%Save data
if (file.exists("output/results.RData")) {
load("output/results.RData")
}
save(no_ChIP,
no_ChIP_rna,
no_ChIP_split,
no_ChIP_split_a,
no_ChIP_split_rna,
no_ChIP_split_rna_a,
no_ChIP_rna_cutoff,
no_ChIP_split_rna_cutoff,
no_ChIP_split_rna_cutoff_a,
no_ChIP_bg_all,
no_ChIP_rna_bg_all,
no_ChIP_split_bg_all,
no_ChIP_split_bg_all_a,
no_ChIP_split_rna_bg_all,
no_ChIP_split_rna_bg_all_a,
no_ChIP_rna_cutoff_bg_all,
no_ChIP_split_rna_cutoff_bg_all,
no_ChIP_split_rna_cutoff_bg_all_a,
with_ChIP,
with_ChIP_rna,
with_ChIP_split,
with_ChIP_split_a,
with_ChIP_split_rna,
with_ChIP_split_rna_a,
with_ChIP_rna_cutoff,
with_ChIP_split_rna_cutoff,
with_ChIP_split_rna_cutoff_a,
with_ChIP_bg_all,
with_ChIP_rna_bg_all,
with_ChIP_split_bg_all,
with_ChIP_split_bg_all_a,
with_ChIP_split_rna_bg_all,
with_ChIP_split_rna_bg_all_a,
with_ChIP_rna_cutoff_bg_all,
with_ChIP_split_rna_cutoff_bg_all,
with_ChIP_split_rna_cutoff_bg_all_a,
file = "output/results.RData"
)SessionInfo
─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 3.6.2 (2019-12-12)
os Ubuntu 16.04.6 LTS
system x86_64, linux-gnu
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Europe/Zurich
date 2020-08-06
─ Packages ───────────────────────────────────────────────────────────────────
package * version date lib
assertthat 0.2.1 2019-03-21 [1]
backports 1.1.8 2020-06-17 [1]
Biobase * 2.46.0 2019-10-29 [1]
BiocGenerics * 0.32.0 2019-10-29 [1]
BiocParallel * 1.20.1 2019-12-21 [1]
bitops 1.0-6 2013-08-17 [1]
bookdown 0.20 2020-06-23 [1]
callr 3.4.3 2020-03-28 [1]
cli 2.0.2 2020-02-28 [1]
crayon 1.3.4 2017-09-16 [1]
DelayedArray * 0.12.3 2020-04-09 [1]
desc 1.2.0 2018-05-01 [1]
devtools 2.3.1 2020-07-21 [1]
digest 0.6.25 2020-02-23 [1]
dplyr * 1.0.0 2020-05-29 [1]
ellipsis 0.3.1 2020-05-15 [1]
evaluate 0.14 2019-05-28 [1]
fansi 0.4.1 2020-01-08 [1]
fs 1.4.2 2020-06-30 [1]
generics 0.0.2 2018-11-29 [1]
GenomeInfoDb * 1.22.1 2020-03-27 [1]
GenomeInfoDbData 1.2.2 2019-11-18 [1]
GenomicRanges * 1.38.0 2019-10-29 [1]
GetoptLong 1.0.2 2020-07-06 [1]
GlobalOptions 0.1.2 2020-06-10 [1]
glue 1.4.1 2020-05-13 [1]
htmltools 0.5.0 2020-06-16 [1]
insight 0.9.0 2020-07-20 [1]
IRanges * 2.20.2 2020-01-13 [1]
jsonlite 1.7.0 2020-06-25 [1]
knitr 1.29 2020-06-23 [1]
lattice 0.20-41 2020-04-02 [1]
lifecycle 0.2.0 2020-03-06 [1]
magrittr 1.5 2014-11-22 [1]
Matrix 1.2-18 2019-11-27 [1]
matrixStats * 0.56.0 2020-03-13 [1]
memoise 1.1.0.9000 2020-05-06 [1]
pillar 1.4.6 2020-07-10 [1]
pkgbuild 1.1.0 2020-07-13 [1]
pkgconfig 2.0.3 2019-09-22 [1]
pkgload 1.1.0 2020-05-29 [1]
prettyunits 1.1.1 2020-01-24 [1]
processx 3.4.3 2020-07-05 [1]
ps 1.3.3 2020-05-08 [1]
purrr 0.3.4 2020-04-17 [1]
R6 2.4.1 2019-11-12 [1]
RCurl 1.98-1.2 2020-04-18 [1]
remotes 2.2.0 2020-07-21 [1]
report * 0.1.0 2020-03-19 [1]
rGREAT * 1.18.0 2019-10-29 [1]
rjson 0.2.20 2018-06-08 [1]
rlang 0.4.7 2020-07-09 [1]
rmarkdown 2.3 2020-06-18 [1]
rmdformats 0.4.0 2020-06-07 [1]
rprojroot 1.3-2 2018-01-03 [1]
S4Vectors * 0.24.4 2020-04-09 [1]
sessioninfo 1.1.1 2018-11-05 [1]
stringi 1.4.6 2020-02-17 [1]
stringr 1.4.0 2019-02-10 [1]
SummarizedExperiment * 1.16.1 2019-12-19 [1]
testthat 2.3.2 2020-03-02 [1]
tibble 3.0.3 2020-07-10 [1]
tidyselect 1.1.0 2020-05-11 [1]
usethis 1.6.1 2020-04-29 [1]
vctrs 0.3.2 2020-07-15 [1]
withr 2.2.0 2020-04-20 [1]
writexl 1.3 2020-05-05 [1]
xfun 0.16 2020-07-24 [1]
XVector 0.26.0 2019-10-29 [1]
yaml 2.2.1 2020-02-01 [1]
zlibbioc 1.32.0 2019-10-29 [1]
source
CRAN (R 3.6.1)
CRAN (R 3.6.2)
Bioconductor
Bioconductor
Bioconductor
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
Bioconductor
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
Bioconductor
Bioconductor
Bioconductor
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
Bioconductor
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
CRAN (R 3.6.1)
CRAN (R 3.6.2)
Github (r-lib/memoise@4aefd9f)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
Github (easystats/report@dcdd283)
Bioconductor
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
Github (juba/rmdformats@94cd7a3)
CRAN (R 3.6.1)
Bioconductor
CRAN (R 3.6.1)
CRAN (R 3.6.2)
CRAN (R 3.6.1)
Bioconductor
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
CRAN (R 3.6.2)
Bioconductor
CRAN (R 3.6.2)
Bioconductor
[1] /home/ubuntu/R/x86_64-pc-linux-gnu-library/3.6
[2] /usr/local/lib/R/site-library
[3] /usr/lib/R/site-library
[4] /usr/lib/R/library